Collaborative Research: SDCI HPC Improvement: Improvement and Support of Community Based Dense Linear Algebra Software for Extreme Scale Computational Science

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Numerous recent federal and academic reports comment on the inadequacy of software support for High Performance Computing. Among other deficiencies, much of the software designed for HPC, such as numerical libraries that encapsulate complicated and widely used algorithms, is considered too hard to use, too inefficient (too low a fraction of peak and/or not scalable), or both. However, the linear algebra libraries LAPACK and ScaLAPACK are frequently mentioned as positive examples whose success in this area should be emulated.This work involves the maintenance, enhancement, hardening, and modernizing of the LAPACK and ScaLAPACK libraries in the context of the ongoing revolution in processor architecture and system design. These libraries are widely used: there were over 160 million web hits (excluding bots) from 2004-2009, and they have been adopted by many vendors as the basis of their own libraries: Intel, Cray, IBM, HP, Fujitsu, NEC, NAG, IMSL, and the Mathworks (producers of Matlab). There is every reason to believe, therefore, that improving these stalwart components of the HPC software stack will have a very large impact.